Cluster Analysis and Discriminant Analysis for Grouping Provinces Based on Factors Affecting Poverty Levels in Indonesia 2018-2020

Abstract

Poverty is a condition that occurs due to the inability of a person or group to meet the minimum basic needs, such as food, clothing, health, housing, and education, which are necessary to maintain survival. The poverty level of an area is influenced by various factors, including the Open Unemployment Rate (TPT), the Provincial Minimum Wage (UMP), and the Human Development Index (IPM). This research aims to group provinces in Indonesia based on factors that affect poverty and determine the discriminatory function of the group formed. The analysis method used is cluster analysis to group provinces into several poverty level groups and discriminatory analysis to form a separating function between the groups. The results of cluster analysis show the formation of three groups, namely the group with the highest poverty level consisting of 7 provinces, the group with moderate poverty level consisting of 8 provinces, and the group with the lowest poverty level which includes other provinces. Furthermore, discriminant analysis produces a discriminant function that is able to distinguish between poverty levels quite well. The results of this research are expected to be considered by the government in formulating poverty alleviation policies that are more on target